RocCurve
One vs rest ROC curve per class, with the AUC annotated.
ROC AUC already exists as a metric because it is a single number. The curve is the shape that number condenses: it shows where along the operating range the model trades false positives for true positives, so two models with equal AUC can be told apart by which end of the range they are good at.
References
Methods
compute(self, y_true, y_pred, class_names: Optional[List[str]] = None) -> List[DashAI.back.core.artifacts.Artifact]
RocCurveBuild the one vs rest ROC curves.
Parameters
- y_true : ndarray
- Encoded true class indexes.
- y_pred : ndarray
- Class probability matrix.
- class_names : Optional[List[str]]
- Class labels in encoded order.
Returns
- List[Artifact]
- A single figure holding one curve per class plus the chance line.
get_credential(self, name: str)
ConfigObjectResolve a registered credential component by name.
Parameters
- name : str
- Credential component class name (e.g. "HuggingFaceCredential").
Returns
- BaseCredential
- An instance of the requested credential component.
get_metadata(cls) -> Dict[str, Any]
BaseReportGet metadata values for the current report.
Returns
- Dict[str, Any]
- UI metadata, including whether the report needs a model that outputs class probabilities.
get_schema(cls) -> dict
ConfigObjectGenerates the component related Json Schema.
Returns
- dict
- Dictionary representing the Json Schema of the component.
validate_and_transform(self, raw_data: dict) -> dict
ConfigObjectIt takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Parameters
- raw_data : dict
- A dictionary with the data provided by the user to initialize the model.
Returns
- dict
- A validated dictionary with the necessary objects.